•We don’t consider potential uses in more detail (jobplacement, replica selection) because we don’tknow if it will happen!

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Network AwareScheduling (v)

•There are some–ve feelings:

–“The network is not a problem. Over-provisioning will always keep us ahead. Either thator fibre and GigE everywhere”

–Report

of the International Grid Performance Workshop 2005 concluded that"Performance simply is not on the critical path for many application projects.Applications that struggle to get code to execute correctly simply do not considerwhether they are using resources efficiently or achieving good performance“

–Personal experience suggests that there is so much to think about elsewhere, that thenetwork is often the last thing to be considered

•Right now, Grid apps rely on the network being good, with no real checks

–by default, rank = estimation of the time interval between the being job submitted andexecution actually beginning

–a function of the number of running and queued jobs at each CE

•SeegLite User Guide

for more info

•As already stated, the presence of replicas of data increases the number of CEs“close” to the data which can potentially execute the job

•But decisions are still made on the static declaration of “close” SEs

•Users are able to re-write the site selection code themselves

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Difference 1

So, difference 1…

The Gridmay

use network performancedata to improve its decision making

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Difference 2

Difference 2…

The Gridwill

exercise the network

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Qualitative View

•By it’s very nature…

–sharing lots of resources to build powerful “systems”…

–to process complex, large data sets…

–in geographically distributed teams

–some in real-time, e.g. visualisation

–so far there has been lots of “embarrassingly parallel” problems(completely independent tasks which can be executed in parallel)but what about tasks requiring inter-processor communication(MPI, Message Passing Interface)?

•…=a lot of data

moving across the network:

–high bandwidth

–low-latency

–stable and guaranteed transmission rates

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Quantitative View (i)

•The Large Hadron Collideris a collection of fourexperiments based atCERN (ALICE, ATLAS,CMS and LHCb) that willmonitor the collision ofaccelerated particles

•≈ 15 Petabytes of datagenerated every year

•Around 100,000 standardCPUs required to process

•GridPP (UK) iscontributing the equivalentof 10,000 PCs

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Quantitative View (ii)

•My understanding is that the LHC when operational, will be pushingout 700 Mbytes/s (≈ 5 Gbps) from the Tier-0 to each Tier-1

•11 Tier-1s, linked to CERN with 10 Gbps Optical Private Network

•So no problems there

•Additional variable flows ≤ 4 Gbps are expected between the Tier-1s

•What about Tier-1s to Tier-2s?

•> 150 Tier-2s, 18 in UK

•Tier-1s and Tier-2s currently linked by standard research networks

•Are you going to commission dedicated fibres or lambdas for each?

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Quantitative View (iii)

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Rolls Royce Networks

•Lots of projects working on adding extraintelligence into the network, and/or interfacing Gridapplications with network control plane for auto-provisioning of dedicated bandwidth: